Generative Artificial Intelligence-based Clinical Decision Support in Patient Data Collection and Analysis, in Physiological Parameter Monitoring, and in Image-based Disease Diagnosis.

• Author: Kucera, Jiri

1. Introduction

   ChatGPT provide precise and reproducible answers and resource of information in terms of accuracy and readability, enhance patient outcomes, health literacy, and quality of care. The purpose of our systematic review is to examine the recently published literature on generative artificial intelligence-based clinical decision support and integrate the insights it configures on patient data collection and analysis, on physiological parameter monitoring, and on image-based disease diagnosis. By analyzing the most recent (2023) and significant (Web of Science, Scopus, and ProQuest) sources, our paper has attempted to prove that generative artificial intelligence and reinforcement learning algorithms (Andronie et al, 2021a; Lewkowich, 2022; Popescu et al., 2017a; Watson, 2022) can enhance well-formulated clinical decision support and practice in learning healthcare systems through accurate responses while inspecting massive volumes of medical data. The actuality and novelty of this study are articulated by addressing how ChatGPT is instrumental in clinical decision support, in medical record abstraction, and in treatment recommendation provision by inspecting massive quantities of patient data, that is an emerging topic involving much interest. Our research problem is whether generative artificial intelligence technologies (Andronie et al., 2021b; Musova et al, 2021; Popescu et al, 2017b) can assist in timely and accurate clinical diagnosis procedures and treatment planning, and in medical knowledge and support.

   In this review, prior findings have been cumulated indicating that generative artificial intelligence technologies (Cegarra Navarro et al, 2023; Nica, 2017; Popescu, 2018) can assist in patient outcome optimization through virtual health assistance and visual computing algorithms. The identified gaps advance how generative artificial intelligence algorithms and machine learning techniques (Glogovetan et al, 2022; Nica, 2018; Valaskova et al, 2022) can optimize patient adherence and engagement. Our main objective is to indicate that ChatGPT can facilitate coherent communication and coordination (Kliestik et al., 2020; Pera, 2022; Peters et al., 2023; Vatamanescu et al, 2022) among healthcare professionals and patients, and clinical decisionmaking precision and efficiency.

2. Theoretical Overview of the Main Concepts

   Generative artificial intelligence algorithms further technology-integrated healthcare system and enhance digital literacy by use of formative or summative evaluations in medical education and practice. Generative artificial intelligence algorithms and machine learning techniques can support clinical decisions and image-based disease diagnosis, handling and interpreting medical data efficiently. ChatGPT can provide radiographic examinations, clinical decision support, fluent, coherent health-related content and patient data summarization, and operative procedures. ChatGPT can design targeted guidance as regards clinical cases, integrating patient histories, diagnoses, and treatment options, and can develop engaging conversation-based lessons in relation to complex medical problems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), ChatGPT can design targeted guidance as regards clinical cases (section 4), generative artificial intelligence technologies can assist in timely and accurate clinical diagnosis procedures and treatment planning (section 5), ChatGPT can facilitate coherent communication and coordination among healthcare professionals and patients (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10).

3. Methodology

   We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March 2023, with search terms including "generative artificial intelligence-based clinical decision support" + "patient data collection and analysis," "physiological parameter monitoring," and "image-based disease diagnosis." As we analyzed research published in 2023, only 173 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 44, chiefly empirical, sources (Tables 1 and 2). Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Distiller SR, ROBIS, and SRDR (Figures 1-6).

4. ChatGPT Can Design Targeted Guidance as Regards Clinical Cases

   ChatGPT can be an efficient contextual and simulation-based decision support tool in singling out imaging examinations and in producing medical referrals (Barash et al., 2023; Juhi et al., 2023; Lee, 2023; Sanmarchi et al., 2023; Vaishya et al., 2023), shaping patient management through useful prognostic information in the emergency department in terms of clinical relevance and clarity and differential diagnosis grading. Generative artificial intelligence algorithms and machine learning techniques can support clinical decisions and image-based disease diagnosis, handling and interpreting medical data efficiently.

   ChatGPT and machine learning algorithms can provide comprehensible, relevant, and accurate information to patients reluctant to seek medical professional advice or in situations with limited medical advice access (Abd-alrazaq et al., 2023; Chavez et al., 2023; Levin et al., 2023; Nov et al., 2023; Xie et al., 2023), optimizing medical consultation and patient education and outcomes. ChatGPT can design targeted guidance as regards clinical cases, integrating patient histories, diagnoses, and treatment options, and can develop engaging conversation-based lessons in relation to complex medical problems.

   ChatGPT is instrumental in clinical decision support, in medical record abstraction, and in treatment recommendation provision by inspecting massive quantities of patient data (Barat et al., 2023; Giannos and Delardas, 2023; Kim et al., 2023; Liu et al., 2023; Sallam, 2023), decreasing medical expenses while improving healthcare delivery quality. Generative artificial intelligence and reinforcement learning algorithms can enhance well-formulated clinical decision support and practice in learning healthcare systems through accurate responses while inspecting massive volumes of medical data. (Table 3)

5. Generative Artificial Intelligence Technologies Can Assist in Timely and Accurate Clinical Diagnosis Procedures and Treatment Planning

   ChatGPT can offer general guidance and provide triage support, recommending actions and reducing unnecessary hospital visits (Altamimi et al., 2023; Eggmann et al., 2023; Ge and Lai, 2023; Mallio et al., 2023; Nan et al., 2023), while serving as an educational resource in terms of medical issue prevention, determination, and management through sample size and case diversity optimization. ChatGPT can provide radiographic examinations, clinical decision support, fluent, coherent health-related content and patient data summarization, and operative procedures.

   Generative artificial intelligence algorithms and machine learning techniques can optimize patient adherence and engagement (Cifarelli and Sheehan, 2023; Rasmussen et al., 2023; Samaan et al., 2023; Wen and Wang, 2023), predicting patient outcomes through physiological parameter monitoring, and streamlining patient data gathering and analysis. ChatGPT provide precise and reproducible answers and resource of information in terms of accuracy and readability, enhance patient outcomes, health literacy, and quality of care.

   ChatGPT can assist physicians with regard to accurate, reliable, and relevant health information, diagnosis and treatment, and decision-making support, decreasing medical-related concerns and misconceptions (Johnson et al., 2023; Meo et al., 2023; Rahsepar et al., 2023; Shahsavar and Choudhury, 2023; Zumsteg and Junn, 2023), improving user awareness, and integrating medical knowledge and exemplary practices. Generative artificial intelligence technologies can assist in timely and accurate clinical diagnosis procedures and treatment planning, and in medical knowledge and support. (Table 4)

6. ChatGPT Can Facilitate Coherent Communication and Coordination among Healthcare Professionals and Patients

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